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Università della Svizzera italiana

1.
Mutsanas, Nikos.
Approximability of precedence constrained and *robust*
scheduling problems.

Degree: 2010, Università della Svizzera italiana

URL: http://doc.rero.ch/record/18217

► We study the approximability of scheduling problems in different contexts. We first give a short introduction to the field of scheduling theory and present a…
(more)

Subjects/Keywords: Robust optimization

Record Details Similar Records

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APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6^{th} Edition):

Mutsanas, N. (2010). Approximability of precedence constrained and robust scheduling problems. (Thesis). Università della Svizzera italiana. Retrieved from http://doc.rero.ch/record/18217

Note: this citation may be lacking information needed for this citation format:

Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16^{th} Edition):

Mutsanas, Nikos. “Approximability of precedence constrained and robust scheduling problems.” 2010. Thesis, Università della Svizzera italiana. Accessed November 17, 2019. http://doc.rero.ch/record/18217.

Note: this citation may be lacking information needed for this citation format:

Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7^{th} Edition):

Mutsanas, Nikos. “Approximability of precedence constrained and robust scheduling problems.” 2010. Web. 17 Nov 2019.

Vancouver:

Mutsanas N. Approximability of precedence constrained and robust scheduling problems. [Internet] [Thesis]. Università della Svizzera italiana; 2010. [cited 2019 Nov 17]. Available from: http://doc.rero.ch/record/18217.

Note: this citation may be lacking information needed for this citation format:

Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Mutsanas N. Approximability of precedence constrained and robust scheduling problems. [Thesis]. Università della Svizzera italiana; 2010. Available from: http://doc.rero.ch/record/18217

Not specified: Masters Thesis or Doctoral Dissertation

University of Minnesota

2.
Moulton, Jeffrey.
* Robust* Fragmentation: A Data-Driven Approach to Decision-Making Under Distributional Ambiguity.

Degree: PhD, Mathematics, 2016, University of Minnesota

URL: http://hdl.handle.net/11299/182165

► Decision makers often must consider many different possible future scenarios when they make a decision. A manager must choose inventory levels to maximize profit when…
(more)

Subjects/Keywords: clustering; distributionally robust optimization; fragmentation; newsvendor; robust

Record Details Similar Records

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APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6^{th} Edition):

Moulton, J. (2016). Robust Fragmentation: A Data-Driven Approach to Decision-Making Under Distributional Ambiguity. (Doctoral Dissertation). University of Minnesota. Retrieved from http://hdl.handle.net/11299/182165

Chicago Manual of Style (16^{th} Edition):

Moulton, Jeffrey. “Robust Fragmentation: A Data-Driven Approach to Decision-Making Under Distributional Ambiguity.” 2016. Doctoral Dissertation, University of Minnesota. Accessed November 17, 2019. http://hdl.handle.net/11299/182165.

MLA Handbook (7^{th} Edition):

Moulton, Jeffrey. “Robust Fragmentation: A Data-Driven Approach to Decision-Making Under Distributional Ambiguity.” 2016. Web. 17 Nov 2019.

Vancouver:

Moulton J. Robust Fragmentation: A Data-Driven Approach to Decision-Making Under Distributional Ambiguity. [Internet] [Doctoral dissertation]. University of Minnesota; 2016. [cited 2019 Nov 17]. Available from: http://hdl.handle.net/11299/182165.

Council of Science Editors:

Moulton J. Robust Fragmentation: A Data-Driven Approach to Decision-Making Under Distributional Ambiguity. [Doctoral Dissertation]. University of Minnesota; 2016. Available from: http://hdl.handle.net/11299/182165

Oregon State University

3. Mokhtari, Zahra. Incorporating Uncertainty in Truckload Relay Network Design.

Degree: PhD, Industrial Engineering, 2017, Oregon State University

URL: http://hdl.handle.net/1957/60591

► In a relay network for full truckload (TL) transportation, facilities known as relay points (RPs) serve as exchange points where truck drivers can exchange trailers.…
(more)

Subjects/Keywords: truckload transportation; Robust optimization

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APA (6^{th} Edition):

Mokhtari, Z. (2017). Incorporating Uncertainty in Truckload Relay Network Design. (Doctoral Dissertation). Oregon State University. Retrieved from http://hdl.handle.net/1957/60591

Chicago Manual of Style (16^{th} Edition):

Mokhtari, Zahra. “Incorporating Uncertainty in Truckload Relay Network Design.” 2017. Doctoral Dissertation, Oregon State University. Accessed November 17, 2019. http://hdl.handle.net/1957/60591.

MLA Handbook (7^{th} Edition):

Mokhtari, Zahra. “Incorporating Uncertainty in Truckload Relay Network Design.” 2017. Web. 17 Nov 2019.

Vancouver:

Mokhtari Z. Incorporating Uncertainty in Truckload Relay Network Design. [Internet] [Doctoral dissertation]. Oregon State University; 2017. [cited 2019 Nov 17]. Available from: http://hdl.handle.net/1957/60591.

Council of Science Editors:

Mokhtari Z. Incorporating Uncertainty in Truckload Relay Network Design. [Doctoral Dissertation]. Oregon State University; 2017. Available from: http://hdl.handle.net/1957/60591

Penn State University

4.
Gauthama Sankar, Aswini.
Time Allocation in Projects under Uncertainty: A *Robust*
*Optimization* Approach.

Degree: MS, Industrial Engineering, 2008, Penn State University

URL: https://etda.libraries.psu.edu/catalog/8499

► Traditional models of project management have laid emphasis on scheduling of operations to meet deadlines. The research presented here approaches project management as a resource…
(more)

Subjects/Keywords: Robust Optimization; Project Management; Uncertainty

Record Details Similar Records

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APA (6^{th} Edition):

Gauthama Sankar, A. (2008). Time Allocation in Projects under Uncertainty: A Robust Optimization Approach. (Masters Thesis). Penn State University. Retrieved from https://etda.libraries.psu.edu/catalog/8499

Chicago Manual of Style (16^{th} Edition):

Gauthama Sankar, Aswini. “Time Allocation in Projects under Uncertainty: A Robust Optimization Approach.” 2008. Masters Thesis, Penn State University. Accessed November 17, 2019. https://etda.libraries.psu.edu/catalog/8499.

MLA Handbook (7^{th} Edition):

Gauthama Sankar, Aswini. “Time Allocation in Projects under Uncertainty: A Robust Optimization Approach.” 2008. Web. 17 Nov 2019.

Vancouver:

Gauthama Sankar A. Time Allocation in Projects under Uncertainty: A Robust Optimization Approach. [Internet] [Masters thesis]. Penn State University; 2008. [cited 2019 Nov 17]. Available from: https://etda.libraries.psu.edu/catalog/8499.

Council of Science Editors:

Gauthama Sankar A. Time Allocation in Projects under Uncertainty: A Robust Optimization Approach. [Masters Thesis]. Penn State University; 2008. Available from: https://etda.libraries.psu.edu/catalog/8499

University of Waterloo

5. Lawrence, Liam Shawn Pritchard. The Optimal Steady-State Control Problem.

Degree: 2019, University of Waterloo

URL: http://hdl.handle.net/10012/14510

► Many engineering systems – including electrical power networks, chemical processing plants, and communication networks – have a well-defined notion of an "optimal'" steady-state operating point.…
(more)

Subjects/Keywords: control theory; robust control; optimization

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APA (6^{th} Edition):

Lawrence, L. S. P. (2019). The Optimal Steady-State Control Problem. (Thesis). University of Waterloo. Retrieved from http://hdl.handle.net/10012/14510

Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16^{th} Edition):

Lawrence, Liam Shawn Pritchard. “The Optimal Steady-State Control Problem.” 2019. Thesis, University of Waterloo. Accessed November 17, 2019. http://hdl.handle.net/10012/14510.

Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7^{th} Edition):

Lawrence, Liam Shawn Pritchard. “The Optimal Steady-State Control Problem.” 2019. Web. 17 Nov 2019.

Vancouver:

Lawrence LSP. The Optimal Steady-State Control Problem. [Internet] [Thesis]. University of Waterloo; 2019. [cited 2019 Nov 17]. Available from: http://hdl.handle.net/10012/14510.

Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Lawrence LSP. The Optimal Steady-State Control Problem. [Thesis]. University of Waterloo; 2019. Available from: http://hdl.handle.net/10012/14510

Not specified: Masters Thesis or Doctoral Dissertation

Texas A&M University

6.
Shah, Utkarsh Dinesh.
An Improved *Robust* *Optimization* Approach for Scheduling Under Uncertainty.

Degree: MS, Chemical Engineering, 2017, Texas A&M University

URL: http://hdl.handle.net/1969.1/165909

► In practice, the uncertainty in processing time data frequently affects the feasibility of optimal solution of the nominal production scheduling problem. Using the unit-specific event-based…
(more)

Subjects/Keywords: Scheduling; Robust Optimization; Multi-stage

Record Details Similar Records

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APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6^{th} Edition):

Shah, U. D. (2017). An Improved Robust Optimization Approach for Scheduling Under Uncertainty. (Masters Thesis). Texas A&M University. Retrieved from http://hdl.handle.net/1969.1/165909

Chicago Manual of Style (16^{th} Edition):

Shah, Utkarsh Dinesh. “An Improved Robust Optimization Approach for Scheduling Under Uncertainty.” 2017. Masters Thesis, Texas A&M University. Accessed November 17, 2019. http://hdl.handle.net/1969.1/165909.

MLA Handbook (7^{th} Edition):

Shah, Utkarsh Dinesh. “An Improved Robust Optimization Approach for Scheduling Under Uncertainty.” 2017. Web. 17 Nov 2019.

Vancouver:

Shah UD. An Improved Robust Optimization Approach for Scheduling Under Uncertainty. [Internet] [Masters thesis]. Texas A&M University; 2017. [cited 2019 Nov 17]. Available from: http://hdl.handle.net/1969.1/165909.

Council of Science Editors:

Shah UD. An Improved Robust Optimization Approach for Scheduling Under Uncertainty. [Masters Thesis]. Texas A&M University; 2017. Available from: http://hdl.handle.net/1969.1/165909

Columbia University

7.
Kang, Yang.
Distributionally *Robust* *Optimization* and its Applications in Machine Learning.

Degree: 2017, Columbia University

URL: https://doi.org/10.7916/D8WD4C1R

► The goal of Distributionally *Robust* *Optimization* (DRO) is to minimize the cost of running a stochastic system, under the assumption that an adversary can replace…
(more)

Subjects/Keywords: Statistics; Robust optimization; Machine learning; Mathematical optimization

Record Details Similar Records

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APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6^{th} Edition):

Kang, Y. (2017). Distributionally Robust Optimization and its Applications in Machine Learning. (Doctoral Dissertation). Columbia University. Retrieved from https://doi.org/10.7916/D8WD4C1R

Chicago Manual of Style (16^{th} Edition):

Kang, Yang. “Distributionally Robust Optimization and its Applications in Machine Learning.” 2017. Doctoral Dissertation, Columbia University. Accessed November 17, 2019. https://doi.org/10.7916/D8WD4C1R.

MLA Handbook (7^{th} Edition):

Kang, Yang. “Distributionally Robust Optimization and its Applications in Machine Learning.” 2017. Web. 17 Nov 2019.

Vancouver:

Kang Y. Distributionally Robust Optimization and its Applications in Machine Learning. [Internet] [Doctoral dissertation]. Columbia University; 2017. [cited 2019 Nov 17]. Available from: https://doi.org/10.7916/D8WD4C1R.

Council of Science Editors:

Kang Y. Distributionally Robust Optimization and its Applications in Machine Learning. [Doctoral Dissertation]. Columbia University; 2017. Available from: https://doi.org/10.7916/D8WD4C1R

University of Toronto

8.
Kaw, Neal.
Inverse linear *optimization* for the recovery of constraint parameters in *robust* and non-*robust* problems.

Degree: 2017, University of Toronto

URL: http://hdl.handle.net/1807/79311

►

Most inverse *optimization* models impute unspecified parameters of an objective function to make an observed solution optimal for a given *optimization* problem. In this thesis,…
(more)

Subjects/Keywords: Inverse optimization; Nonlinear programming; Robust optimization; 0796

Record Details Similar Records

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APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6^{th} Edition):

Kaw, N. (2017). Inverse linear optimization for the recovery of constraint parameters in robust and non-robust problems. (Masters Thesis). University of Toronto. Retrieved from http://hdl.handle.net/1807/79311

Chicago Manual of Style (16^{th} Edition):

Kaw, Neal. “Inverse linear optimization for the recovery of constraint parameters in robust and non-robust problems.” 2017. Masters Thesis, University of Toronto. Accessed November 17, 2019. http://hdl.handle.net/1807/79311.

MLA Handbook (7^{th} Edition):

Kaw, Neal. “Inverse linear optimization for the recovery of constraint parameters in robust and non-robust problems.” 2017. Web. 17 Nov 2019.

Vancouver:

Kaw N. Inverse linear optimization for the recovery of constraint parameters in robust and non-robust problems. [Internet] [Masters thesis]. University of Toronto; 2017. [cited 2019 Nov 17]. Available from: http://hdl.handle.net/1807/79311.

Council of Science Editors:

Kaw N. Inverse linear optimization for the recovery of constraint parameters in robust and non-robust problems. [Masters Thesis]. University of Toronto; 2017. Available from: http://hdl.handle.net/1807/79311

Loughborough University

9.
Rossetti, Gaia.
Mathematical *optimization* techniques for cognitive radar networks.

Degree: PhD, 2018, Loughborough University

URL: https://dspace.lboro.ac.uk/2134/33419 ; https://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.747937

► This thesis discusses mathematical *optimization* techniques for waveform design in cognitive radars. These techniques have been designed with an increasing level of sophistication, starting from…
(more)

Subjects/Keywords: Waveform optimization; Convex optimization; Robust optimization; Cognitive radars

Record Details Similar Records

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APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6^{th} Edition):

Rossetti, G. (2018). Mathematical optimization techniques for cognitive radar networks. (Doctoral Dissertation). Loughborough University. Retrieved from https://dspace.lboro.ac.uk/2134/33419 ; https://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.747937

Chicago Manual of Style (16^{th} Edition):

Rossetti, Gaia. “Mathematical optimization techniques for cognitive radar networks.” 2018. Doctoral Dissertation, Loughborough University. Accessed November 17, 2019. https://dspace.lboro.ac.uk/2134/33419 ; https://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.747937.

MLA Handbook (7^{th} Edition):

Rossetti, Gaia. “Mathematical optimization techniques for cognitive radar networks.” 2018. Web. 17 Nov 2019.

Vancouver:

Rossetti G. Mathematical optimization techniques for cognitive radar networks. [Internet] [Doctoral dissertation]. Loughborough University; 2018. [cited 2019 Nov 17]. Available from: https://dspace.lboro.ac.uk/2134/33419 ; https://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.747937.

Council of Science Editors:

Rossetti G. Mathematical optimization techniques for cognitive radar networks. [Doctoral Dissertation]. Loughborough University; 2018. Available from: https://dspace.lboro.ac.uk/2134/33419 ; https://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.747937

Loughborough University

10.
Rossetti, Gaia.
Mathematical *optimization* techniques for cognitive radar networks.

Degree: PhD, 2018, Loughborough University

URL: http://hdl.handle.net/2134/33419

► This thesis discusses mathematical *optimization* techniques for waveform design in cognitive radars. These techniques have been designed with an increasing level of sophistication, starting from…
(more)

Subjects/Keywords: Waveform optimization; Convex optimization; Robust optimization; Cognitive radars

Record Details Similar Records

❌

APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6^{th} Edition):

Rossetti, G. (2018). Mathematical optimization techniques for cognitive radar networks. (Doctoral Dissertation). Loughborough University. Retrieved from http://hdl.handle.net/2134/33419

Chicago Manual of Style (16^{th} Edition):

Rossetti, Gaia. “Mathematical optimization techniques for cognitive radar networks.” 2018. Doctoral Dissertation, Loughborough University. Accessed November 17, 2019. http://hdl.handle.net/2134/33419.

MLA Handbook (7^{th} Edition):

Rossetti, Gaia. “Mathematical optimization techniques for cognitive radar networks.” 2018. Web. 17 Nov 2019.

Vancouver:

Rossetti G. Mathematical optimization techniques for cognitive radar networks. [Internet] [Doctoral dissertation]. Loughborough University; 2018. [cited 2019 Nov 17]. Available from: http://hdl.handle.net/2134/33419.

Council of Science Editors:

Rossetti G. Mathematical optimization techniques for cognitive radar networks. [Doctoral Dissertation]. Loughborough University; 2018. Available from: http://hdl.handle.net/2134/33419

11.
Espinoza García, Juan Carlos.
*Robust**optimization* for discrete structures and non-linear impact of uncertainty : Gouverner ou être gouverné ? : L'agence en conseil de vote, un acteur en construction dans la gouvernance d'entreprise.

Degree: Docteur es, Sciences de gestion, 2017, Cergy-Pontoise, Ecole supérieure des sciences économiques et commerciales

URL: http://www.theses.fr/2017ESEC0004

►

L’objectif de cette thèse est de proposer des solutions efficaces à des problèmes de décision qui ont un impact sur la vie des citoyens, et… (more)

Subjects/Keywords: Optimisation robust; Modèles de choix; Robust optimization; Location problems; Choice models

Record Details Similar Records

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APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6^{th} Edition):

Espinoza García, J. C. (2017). Robust optimization for discrete structures and non-linear impact of uncertainty : Gouverner ou être gouverné ? : L'agence en conseil de vote, un acteur en construction dans la gouvernance d'entreprise. (Doctoral Dissertation). Cergy-Pontoise, Ecole supérieure des sciences économiques et commerciales. Retrieved from http://www.theses.fr/2017ESEC0004

Chicago Manual of Style (16^{th} Edition):

Espinoza García, Juan Carlos. “Robust optimization for discrete structures and non-linear impact of uncertainty : Gouverner ou être gouverné ? : L'agence en conseil de vote, un acteur en construction dans la gouvernance d'entreprise.” 2017. Doctoral Dissertation, Cergy-Pontoise, Ecole supérieure des sciences économiques et commerciales. Accessed November 17, 2019. http://www.theses.fr/2017ESEC0004.

MLA Handbook (7^{th} Edition):

Espinoza García, Juan Carlos. “Robust optimization for discrete structures and non-linear impact of uncertainty : Gouverner ou être gouverné ? : L'agence en conseil de vote, un acteur en construction dans la gouvernance d'entreprise.” 2017. Web. 17 Nov 2019.

Vancouver:

Espinoza García JC. Robust optimization for discrete structures and non-linear impact of uncertainty : Gouverner ou être gouverné ? : L'agence en conseil de vote, un acteur en construction dans la gouvernance d'entreprise. [Internet] [Doctoral dissertation]. Cergy-Pontoise, Ecole supérieure des sciences économiques et commerciales; 2017. [cited 2019 Nov 17]. Available from: http://www.theses.fr/2017ESEC0004.

Council of Science Editors:

Espinoza García JC. Robust optimization for discrete structures and non-linear impact of uncertainty : Gouverner ou être gouverné ? : L'agence en conseil de vote, un acteur en construction dans la gouvernance d'entreprise. [Doctoral Dissertation]. Cergy-Pontoise, Ecole supérieure des sciences économiques et commerciales; 2017. Available from: http://www.theses.fr/2017ESEC0004

Georgia Tech

12.
Lorca Galvez, Alvaro Hugo.
*Robust**optimization* for renewable energy integration in power system operations.

Degree: PhD, Industrial and Systems Engineering, 2016, Georgia Tech

URL: http://hdl.handle.net/1853/55653

► *Optimization* provides critical support for the operation of electric power systems. As power systems evolve, enhanced operational methodologies are required, and innovative *optimization* models have…
(more)

Subjects/Keywords: Robust optimization; Power system operations; Renewable energy

Record Details Similar Records

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APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6^{th} Edition):

Lorca Galvez, A. H. (2016). Robust optimization for renewable energy integration in power system operations. (Doctoral Dissertation). Georgia Tech. Retrieved from http://hdl.handle.net/1853/55653

Chicago Manual of Style (16^{th} Edition):

Lorca Galvez, Alvaro Hugo. “Robust optimization for renewable energy integration in power system operations.” 2016. Doctoral Dissertation, Georgia Tech. Accessed November 17, 2019. http://hdl.handle.net/1853/55653.

MLA Handbook (7^{th} Edition):

Lorca Galvez, Alvaro Hugo. “Robust optimization for renewable energy integration in power system operations.” 2016. Web. 17 Nov 2019.

Vancouver:

Lorca Galvez AH. Robust optimization for renewable energy integration in power system operations. [Internet] [Doctoral dissertation]. Georgia Tech; 2016. [cited 2019 Nov 17]. Available from: http://hdl.handle.net/1853/55653.

Council of Science Editors:

Lorca Galvez AH. Robust optimization for renewable energy integration in power system operations. [Doctoral Dissertation]. Georgia Tech; 2016. Available from: http://hdl.handle.net/1853/55653

Hong Kong University of Science and Technology

13.
Sun, Ying.
Majorization-minimization algorithm and its applications in *robust* covariance matrix estimation.

Degree: 2016, Hong Kong University of Science and Technology

URL: https://doi.org/10.14711/thesis-b1626265 ; http://repository.ust.hk/ir/bitstream/1783.1-86941/1/th_redirect.html

► Covariance estimation has been a fundamental and long existing problem, closely related to various fields including multi-antenna communication systems, social networks, bioinformatics, and financial engineering.…
(more)

Subjects/Keywords: Analysis of covariance; Estimation theory; Robust optimization

Record Details Similar Records

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APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6^{th} Edition):

Sun, Y. (2016). Majorization-minimization algorithm and its applications in robust covariance matrix estimation. (Thesis). Hong Kong University of Science and Technology. Retrieved from https://doi.org/10.14711/thesis-b1626265 ; http://repository.ust.hk/ir/bitstream/1783.1-86941/1/th_redirect.html

Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16^{th} Edition):

Sun, Ying. “Majorization-minimization algorithm and its applications in robust covariance matrix estimation.” 2016. Thesis, Hong Kong University of Science and Technology. Accessed November 17, 2019. https://doi.org/10.14711/thesis-b1626265 ; http://repository.ust.hk/ir/bitstream/1783.1-86941/1/th_redirect.html.

Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7^{th} Edition):

Sun, Ying. “Majorization-minimization algorithm and its applications in robust covariance matrix estimation.” 2016. Web. 17 Nov 2019.

Vancouver:

Sun Y. Majorization-minimization algorithm and its applications in robust covariance matrix estimation. [Internet] [Thesis]. Hong Kong University of Science and Technology; 2016. [cited 2019 Nov 17]. Available from: https://doi.org/10.14711/thesis-b1626265 ; http://repository.ust.hk/ir/bitstream/1783.1-86941/1/th_redirect.html.

Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Sun Y. Majorization-minimization algorithm and its applications in robust covariance matrix estimation. [Thesis]. Hong Kong University of Science and Technology; 2016. Available from: https://doi.org/10.14711/thesis-b1626265 ; http://repository.ust.hk/ir/bitstream/1783.1-86941/1/th_redirect.html

Not specified: Masters Thesis or Doctoral Dissertation

Lehigh University

14.
Dong, Yang.
* Robust* Performance Attribution Analysis in Investment Management.

Degree: PhD, Information and Systems Engineering, 2014, Lehigh University

URL: https://preserve.lehigh.edu/etd/1474

► This dissertation investigates *robust* *optimization* models for performance attribution analysis in investment management. Specifically, an investment manager seeks to evaluate the performance of fund managers…
(more)

Subjects/Keywords: Portfolio management; Robust optimization; Uncertainty; Engineering

Record Details Similar Records

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APA (6^{th} Edition):

Dong, Y. (2014). Robust Performance Attribution Analysis in Investment Management. (Doctoral Dissertation). Lehigh University. Retrieved from https://preserve.lehigh.edu/etd/1474

Chicago Manual of Style (16^{th} Edition):

Dong, Yang. “Robust Performance Attribution Analysis in Investment Management.” 2014. Doctoral Dissertation, Lehigh University. Accessed November 17, 2019. https://preserve.lehigh.edu/etd/1474.

MLA Handbook (7^{th} Edition):

Dong, Yang. “Robust Performance Attribution Analysis in Investment Management.” 2014. Web. 17 Nov 2019.

Vancouver:

Dong Y. Robust Performance Attribution Analysis in Investment Management. [Internet] [Doctoral dissertation]. Lehigh University; 2014. [cited 2019 Nov 17]. Available from: https://preserve.lehigh.edu/etd/1474.

Council of Science Editors:

Dong Y. Robust Performance Attribution Analysis in Investment Management. [Doctoral Dissertation]. Lehigh University; 2014. Available from: https://preserve.lehigh.edu/etd/1474

Mississippi State University

15. Baez-Rivera, Yamilka Isabel. CONTROL OF MULTIGENERATORS FOR THE ALL-ELECTRIC SHIP.

Degree: PhD, Electrical and Computer Engineering, 2011, Mississippi State University

URL: http://sun.library.msstate.edu/ETD-db/theses/available/etd-04042011-173542/ ;

► <p class=Basictextdouble-spaced>The next generation of U.S. Navy ships will see the integration of the propulsion and electrical systems as part of the all-electric ship.<span style='mso-spacerun:yes'>…
(more)

Subjects/Keywords: optimization; stability; shipboard power systems; robust control

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APA (6^{th} Edition):

Baez-Rivera, Y. I. (2011). CONTROL OF MULTIGENERATORS FOR THE ALL-ELECTRIC SHIP. (Doctoral Dissertation). Mississippi State University. Retrieved from http://sun.library.msstate.edu/ETD-db/theses/available/etd-04042011-173542/ ;

Chicago Manual of Style (16^{th} Edition):

Baez-Rivera, Yamilka Isabel. “CONTROL OF MULTIGENERATORS FOR THE ALL-ELECTRIC SHIP.” 2011. Doctoral Dissertation, Mississippi State University. Accessed November 17, 2019. http://sun.library.msstate.edu/ETD-db/theses/available/etd-04042011-173542/ ;.

MLA Handbook (7^{th} Edition):

Baez-Rivera, Yamilka Isabel. “CONTROL OF MULTIGENERATORS FOR THE ALL-ELECTRIC SHIP.” 2011. Web. 17 Nov 2019.

Vancouver:

Baez-Rivera YI. CONTROL OF MULTIGENERATORS FOR THE ALL-ELECTRIC SHIP. [Internet] [Doctoral dissertation]. Mississippi State University; 2011. [cited 2019 Nov 17]. Available from: http://sun.library.msstate.edu/ETD-db/theses/available/etd-04042011-173542/ ;.

Council of Science Editors:

Baez-Rivera YI. CONTROL OF MULTIGENERATORS FOR THE ALL-ELECTRIC SHIP. [Doctoral Dissertation]. Mississippi State University; 2011. Available from: http://sun.library.msstate.edu/ETD-db/theses/available/etd-04042011-173542/ ;

Columbia University

16. Qu, Qing. Nonconvex Recovery of Low-complexity Models.

Degree: 2018, Columbia University

URL: https://doi.org/10.7916/D8TJ04K8

► Today we are living in the era of big data, there is a pressing need for efficient, scalable and *robust* *optimization* methods to analyze the…
(more)

Subjects/Keywords: Electrical engineering; Nonconvex programming; Robust optimization

Record Details Similar Records

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APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6^{th} Edition):

Qu, Q. (2018). Nonconvex Recovery of Low-complexity Models. (Doctoral Dissertation). Columbia University. Retrieved from https://doi.org/10.7916/D8TJ04K8

Chicago Manual of Style (16^{th} Edition):

Qu, Qing. “Nonconvex Recovery of Low-complexity Models.” 2018. Doctoral Dissertation, Columbia University. Accessed November 17, 2019. https://doi.org/10.7916/D8TJ04K8.

MLA Handbook (7^{th} Edition):

Qu, Qing. “Nonconvex Recovery of Low-complexity Models.” 2018. Web. 17 Nov 2019.

Vancouver:

Qu Q. Nonconvex Recovery of Low-complexity Models. [Internet] [Doctoral dissertation]. Columbia University; 2018. [cited 2019 Nov 17]. Available from: https://doi.org/10.7916/D8TJ04K8.

Council of Science Editors:

Qu Q. Nonconvex Recovery of Low-complexity Models. [Doctoral Dissertation]. Columbia University; 2018. Available from: https://doi.org/10.7916/D8TJ04K8

University of Pennsylvania

17.
Fazlyab, Mahyar.
Control Theoretic Methods In Analysis And Design Of *Optimization* Algorithms.

Degree: 2018, University of Pennsylvania

URL: https://repository.upenn.edu/edissertations/3066

► Recently, there has been a surge of interest in incorporating tools from dynamical systems and control theory to analyze and design iterative *optimization* algorithms. This…
(more)

Subjects/Keywords: Iterative Algorithms; Numerical Optimization; Robust Control; Engineering

Record Details Similar Records

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APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6^{th} Edition):

Fazlyab, M. (2018). Control Theoretic Methods In Analysis And Design Of Optimization Algorithms. (Thesis). University of Pennsylvania. Retrieved from https://repository.upenn.edu/edissertations/3066

Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16^{th} Edition):

Fazlyab, Mahyar. “Control Theoretic Methods In Analysis And Design Of Optimization Algorithms.” 2018. Thesis, University of Pennsylvania. Accessed November 17, 2019. https://repository.upenn.edu/edissertations/3066.

Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7^{th} Edition):

Fazlyab, Mahyar. “Control Theoretic Methods In Analysis And Design Of Optimization Algorithms.” 2018. Web. 17 Nov 2019.

Vancouver:

Fazlyab M. Control Theoretic Methods In Analysis And Design Of Optimization Algorithms. [Internet] [Thesis]. University of Pennsylvania; 2018. [cited 2019 Nov 17]. Available from: https://repository.upenn.edu/edissertations/3066.

Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Fazlyab M. Control Theoretic Methods In Analysis And Design Of Optimization Algorithms. [Thesis]. University of Pennsylvania; 2018. Available from: https://repository.upenn.edu/edissertations/3066

Not specified: Masters Thesis or Doctoral Dissertation

University of Oregon

18.
Torkamani, MohamadAli.
* Robust* Large Margin Approaches for Machine Learning in Adversarial Settings.

Degree: 2016, University of Oregon

URL: http://hdl.handle.net/1794/20677

► Machine learning algorithms are invented to learn from data and to use data to perform predictions and analyses. Many agencies are now using machine learning…
(more)

Subjects/Keywords: Adversarial machine learning; Convex optimization; Customized regularization; Dropout; Robust machine learning; Robust optimization

Record Details Similar Records

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APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6^{th} Edition):

Torkamani, M. (2016). Robust Large Margin Approaches for Machine Learning in Adversarial Settings. (Thesis). University of Oregon. Retrieved from http://hdl.handle.net/1794/20677

Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16^{th} Edition):

Torkamani, MohamadAli. “Robust Large Margin Approaches for Machine Learning in Adversarial Settings.” 2016. Thesis, University of Oregon. Accessed November 17, 2019. http://hdl.handle.net/1794/20677.

Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7^{th} Edition):

Torkamani, MohamadAli. “Robust Large Margin Approaches for Machine Learning in Adversarial Settings.” 2016. Web. 17 Nov 2019.

Vancouver:

Torkamani M. Robust Large Margin Approaches for Machine Learning in Adversarial Settings. [Internet] [Thesis]. University of Oregon; 2016. [cited 2019 Nov 17]. Available from: http://hdl.handle.net/1794/20677.

Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Torkamani M. Robust Large Margin Approaches for Machine Learning in Adversarial Settings. [Thesis]. University of Oregon; 2016. Available from: http://hdl.handle.net/1794/20677

Not specified: Masters Thesis or Doctoral Dissertation

University of Lund

19.
Knutson, Hans-Kristian.
* Robust* Multi-objective

Degree: 2016, University of Lund

URL: http://lup.lub.lu.se/record/a0e0e46e-754d-41c3-919e-852021c47b8f ; http://portal.research.lu.se/ws/files/7726935/Thesis_Hans_Kristian_Knutson_spikfil_utan_papers.pdf

► Rare earth elements comprise the metallic elements known as lanthanides as well as scandium and yttrium. They are extensively used in modern technological industries and…
(more)

Subjects/Keywords: Kemiteknik; Chromatography; Rare earth elements; Modeling; Multi-objective optimization; Robust optimization; Chromatography; Rare earth elements; Modeling; Multi-objective optimization; Robust optimization

Record Details Similar Records

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APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6^{th} Edition):

Knutson, H. (2016). Robust Multi-objective Optimization of Rare Earth Element Chromatography. (Doctoral Dissertation). University of Lund. Retrieved from http://lup.lub.lu.se/record/a0e0e46e-754d-41c3-919e-852021c47b8f ; http://portal.research.lu.se/ws/files/7726935/Thesis_Hans_Kristian_Knutson_spikfil_utan_papers.pdf

Chicago Manual of Style (16^{th} Edition):

Knutson, Hans-Kristian. “Robust Multi-objective Optimization of Rare Earth Element Chromatography.” 2016. Doctoral Dissertation, University of Lund. Accessed November 17, 2019. http://lup.lub.lu.se/record/a0e0e46e-754d-41c3-919e-852021c47b8f ; http://portal.research.lu.se/ws/files/7726935/Thesis_Hans_Kristian_Knutson_spikfil_utan_papers.pdf.

MLA Handbook (7^{th} Edition):

Knutson, Hans-Kristian. “Robust Multi-objective Optimization of Rare Earth Element Chromatography.” 2016. Web. 17 Nov 2019.

Vancouver:

Knutson H. Robust Multi-objective Optimization of Rare Earth Element Chromatography. [Internet] [Doctoral dissertation]. University of Lund; 2016. [cited 2019 Nov 17]. Available from: http://lup.lub.lu.se/record/a0e0e46e-754d-41c3-919e-852021c47b8f ; http://portal.research.lu.se/ws/files/7726935/Thesis_Hans_Kristian_Knutson_spikfil_utan_papers.pdf.

Council of Science Editors:

Knutson H. Robust Multi-objective Optimization of Rare Earth Element Chromatography. [Doctoral Dissertation]. University of Lund; 2016. Available from: http://lup.lub.lu.se/record/a0e0e46e-754d-41c3-919e-852021c47b8f ; http://portal.research.lu.se/ws/files/7726935/Thesis_Hans_Kristian_Knutson_spikfil_utan_papers.pdf

University of Waterloo

20.
Ripsman, Danielle.
* Robust* Direct Aperture

Degree: 2018, University of Waterloo

URL: http://hdl.handle.net/10012/13958

► Designing conformal and equipment-compatible radiation therapy plans is essential for ensuring high-quality treatment outcomes for cancer patients. Intensity modulated radiation therapy (IMRT) is a commonly-used…
(more)

Subjects/Keywords: Radiation Therapy; Optimization; Direct Aperture Optimization; Robust Optimization; IMRT; Breast Cancer; Robust Direct Aperture Optimization; DAO; RDAO

Record Details Similar Records

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APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6^{th} Edition):

Ripsman, D. (2018). Robust Direct Aperture Optimization Methods for Cardiac Sparing in Left-Sided Breast Cancer Radiation Therapy. (Thesis). University of Waterloo. Retrieved from http://hdl.handle.net/10012/13958

Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16^{th} Edition):

Ripsman, Danielle. “Robust Direct Aperture Optimization Methods for Cardiac Sparing in Left-Sided Breast Cancer Radiation Therapy.” 2018. Thesis, University of Waterloo. Accessed November 17, 2019. http://hdl.handle.net/10012/13958.

Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7^{th} Edition):

Ripsman, Danielle. “Robust Direct Aperture Optimization Methods for Cardiac Sparing in Left-Sided Breast Cancer Radiation Therapy.” 2018. Web. 17 Nov 2019.

Vancouver:

Ripsman D. Robust Direct Aperture Optimization Methods for Cardiac Sparing in Left-Sided Breast Cancer Radiation Therapy. [Internet] [Thesis]. University of Waterloo; 2018. [cited 2019 Nov 17]. Available from: http://hdl.handle.net/10012/13958.

Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Ripsman D. Robust Direct Aperture Optimization Methods for Cardiac Sparing in Left-Sided Breast Cancer Radiation Therapy. [Thesis]. University of Waterloo; 2018. Available from: http://hdl.handle.net/10012/13958

Not specified: Masters Thesis or Doctoral Dissertation

Penn State University

21. Solo, Christopher James. MULTI-OBJECTIVE, INTEGRATED SUPPLY CHAIN DESIGN AND OPERATION UNDER UNCERTAINTY.

Degree: PhD, Industrial Engineering, 2009, Penn State University

URL: https://etda.libraries.psu.edu/catalog/9709

► This research involves the development of a flexible, multi-objective *optimization* tool for use by supply chain managers in the design and operation of manufacturing-distribution networks…
(more)

Subjects/Keywords: supply chain; uncertainty; stochastic optimization; robust optimization; chance-constrained goal programming

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APA (6^{th} Edition):

Solo, C. J. (2009). MULTI-OBJECTIVE, INTEGRATED SUPPLY CHAIN DESIGN AND OPERATION UNDER UNCERTAINTY. (Doctoral Dissertation). Penn State University. Retrieved from https://etda.libraries.psu.edu/catalog/9709

Chicago Manual of Style (16^{th} Edition):

Solo, Christopher James. “MULTI-OBJECTIVE, INTEGRATED SUPPLY CHAIN DESIGN AND OPERATION UNDER UNCERTAINTY.” 2009. Doctoral Dissertation, Penn State University. Accessed November 17, 2019. https://etda.libraries.psu.edu/catalog/9709.

MLA Handbook (7^{th} Edition):

Solo, Christopher James. “MULTI-OBJECTIVE, INTEGRATED SUPPLY CHAIN DESIGN AND OPERATION UNDER UNCERTAINTY.” 2009. Web. 17 Nov 2019.

Vancouver:

Solo CJ. MULTI-OBJECTIVE, INTEGRATED SUPPLY CHAIN DESIGN AND OPERATION UNDER UNCERTAINTY. [Internet] [Doctoral dissertation]. Penn State University; 2009. [cited 2019 Nov 17]. Available from: https://etda.libraries.psu.edu/catalog/9709.

Council of Science Editors:

Solo CJ. MULTI-OBJECTIVE, INTEGRATED SUPPLY CHAIN DESIGN AND OPERATION UNDER UNCERTAINTY. [Doctoral Dissertation]. Penn State University; 2009. Available from: https://etda.libraries.psu.edu/catalog/9709

University of Southern California

22. Ye, Wei. Models and algorithms for energy efficient wireless sensor networks.

Degree: PhD, Industrial & Systems Engineering, 2009, University of Southern California

URL: http://digitallibrary.usc.edu/cdm/compoundobject/collection/p15799coll127/id/483963/rec/4151

► Wireless Sensor Networks (WSNs) is an area of active research in industry and academia. WSNs can be used in a wide array of applications such…
(more)

Subjects/Keywords: wireless sensor networks; robust optimization; nonlinear optimization; operations research

Record Details Similar Records

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APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6^{th} Edition):

Ye, W. (2009). Models and algorithms for energy efficient wireless sensor networks. (Doctoral Dissertation). University of Southern California. Retrieved from http://digitallibrary.usc.edu/cdm/compoundobject/collection/p15799coll127/id/483963/rec/4151

Chicago Manual of Style (16^{th} Edition):

Ye, Wei. “Models and algorithms for energy efficient wireless sensor networks.” 2009. Doctoral Dissertation, University of Southern California. Accessed November 17, 2019. http://digitallibrary.usc.edu/cdm/compoundobject/collection/p15799coll127/id/483963/rec/4151.

MLA Handbook (7^{th} Edition):

Ye, Wei. “Models and algorithms for energy efficient wireless sensor networks.” 2009. Web. 17 Nov 2019.

Vancouver:

Ye W. Models and algorithms for energy efficient wireless sensor networks. [Internet] [Doctoral dissertation]. University of Southern California; 2009. [cited 2019 Nov 17]. Available from: http://digitallibrary.usc.edu/cdm/compoundobject/collection/p15799coll127/id/483963/rec/4151.

Council of Science Editors:

Ye W. Models and algorithms for energy efficient wireless sensor networks. [Doctoral Dissertation]. University of Southern California; 2009. Available from: http://digitallibrary.usc.edu/cdm/compoundobject/collection/p15799coll127/id/483963/rec/4151

Columbia University

23.
Lu, Brian Yin.
Essays on Approximation Algorithms for *Robust* Linear *Optimization* Problems.

Degree: 2016, Columbia University

URL: https://doi.org/10.7916/D8ZG6SGM

► Solving *optimization* problems under uncertainty has been an important topic since the appearance of mathematical *optimization* in the mid 19th century. George Dantzig’s 1955 paper,…
(more)

Subjects/Keywords: Mathematical optimization; Uncertainty (Information theory); Robust optimization; Approximation algorithms; Operations research

Record Details Similar Records

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APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6^{th} Edition):

Lu, B. Y. (2016). Essays on Approximation Algorithms for Robust Linear Optimization Problems. (Doctoral Dissertation). Columbia University. Retrieved from https://doi.org/10.7916/D8ZG6SGM

Chicago Manual of Style (16^{th} Edition):

Lu, Brian Yin. “Essays on Approximation Algorithms for Robust Linear Optimization Problems.” 2016. Doctoral Dissertation, Columbia University. Accessed November 17, 2019. https://doi.org/10.7916/D8ZG6SGM.

MLA Handbook (7^{th} Edition):

Lu, Brian Yin. “Essays on Approximation Algorithms for Robust Linear Optimization Problems.” 2016. Web. 17 Nov 2019.

Vancouver:

Lu BY. Essays on Approximation Algorithms for Robust Linear Optimization Problems. [Internet] [Doctoral dissertation]. Columbia University; 2016. [cited 2019 Nov 17]. Available from: https://doi.org/10.7916/D8ZG6SGM.

Council of Science Editors:

Lu BY. Essays on Approximation Algorithms for Robust Linear Optimization Problems. [Doctoral Dissertation]. Columbia University; 2016. Available from: https://doi.org/10.7916/D8ZG6SGM

University of New South Wales

24.
Asafuddoula, Md.
Development of algorithms to solve different key challenges facing design * optimization*.

Degree: Engineering & Information Technology, 2014, University of New South Wales

URL: http://handle.unsw.edu.au/1959.4/53458 ; https://unsworks.unsw.edu.au/fapi/datastream/unsworks:12153/SOURCE02?view=true

► *Optimization* methods play an indispensable role in today’s competitive environmentand there are plenty of practical examples where such methods have been used toidentify better performing…
(more)

Subjects/Keywords: Robust design optimization; Constraint handling; Many objective optimization

Record Details Similar Records

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APA (6^{th} Edition):

Asafuddoula, M. (2014). Development of algorithms to solve different key challenges facing design optimization. (Doctoral Dissertation). University of New South Wales. Retrieved from http://handle.unsw.edu.au/1959.4/53458 ; https://unsworks.unsw.edu.au/fapi/datastream/unsworks:12153/SOURCE02?view=true

Chicago Manual of Style (16^{th} Edition):

Asafuddoula, Md. “Development of algorithms to solve different key challenges facing design optimization.” 2014. Doctoral Dissertation, University of New South Wales. Accessed November 17, 2019. http://handle.unsw.edu.au/1959.4/53458 ; https://unsworks.unsw.edu.au/fapi/datastream/unsworks:12153/SOURCE02?view=true.

MLA Handbook (7^{th} Edition):

Asafuddoula, Md. “Development of algorithms to solve different key challenges facing design optimization.” 2014. Web. 17 Nov 2019.

Vancouver:

Asafuddoula M. Development of algorithms to solve different key challenges facing design optimization. [Internet] [Doctoral dissertation]. University of New South Wales; 2014. [cited 2019 Nov 17]. Available from: http://handle.unsw.edu.au/1959.4/53458 ; https://unsworks.unsw.edu.au/fapi/datastream/unsworks:12153/SOURCE02?view=true.

Council of Science Editors:

Asafuddoula M. Development of algorithms to solve different key challenges facing design optimization. [Doctoral Dissertation]. University of New South Wales; 2014. Available from: http://handle.unsw.edu.au/1959.4/53458 ; https://unsworks.unsw.edu.au/fapi/datastream/unsworks:12153/SOURCE02?view=true

University of Illinois – Urbana-Champaign

25.
Anderson, Jesse Cole.
* Robust* design

Degree: MS, Mechanical Engineering, 2019, University of Illinois – Urbana-Champaign

URL: http://hdl.handle.net/2142/104728

► This thesis develops a framework for performing *robust* design *optimization* of objective functions constrained by differential, algebraic, and integral constraints. A successive parameter continuation method…
(more)

Subjects/Keywords: continuation; optimization; robust optimization; polynomial chaos expansion; Duffing oscillator

Record Details Similar Records

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APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6^{th} Edition):

Anderson, J. C. (2019). Robust design optimization with dynamic constraints using numerical continuation. (Thesis). University of Illinois – Urbana-Champaign. Retrieved from http://hdl.handle.net/2142/104728

Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16^{th} Edition):

Anderson, Jesse Cole. “Robust design optimization with dynamic constraints using numerical continuation.” 2019. Thesis, University of Illinois – Urbana-Champaign. Accessed November 17, 2019. http://hdl.handle.net/2142/104728.

Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7^{th} Edition):

Anderson, Jesse Cole. “Robust design optimization with dynamic constraints using numerical continuation.” 2019. Web. 17 Nov 2019.

Vancouver:

Anderson JC. Robust design optimization with dynamic constraints using numerical continuation. [Internet] [Thesis]. University of Illinois – Urbana-Champaign; 2019. [cited 2019 Nov 17]. Available from: http://hdl.handle.net/2142/104728.

Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Anderson JC. Robust design optimization with dynamic constraints using numerical continuation. [Thesis]. University of Illinois – Urbana-Champaign; 2019. Available from: http://hdl.handle.net/2142/104728

Not specified: Masters Thesis or Doctoral Dissertation

Georgia Tech

26.
Morris, Carl.
Dynamic portfolio *optimization* using mean-semivariance.

Degree: PhD, Industrial and Systems Engineering, 2017, Georgia Tech

URL: http://hdl.handle.net/1853/59245

► This dissertation studies the mean-semivariance portfolio *optimization* problem. We describe the relationship of this kind of *optimization* in the context of other types of portfolio…
(more)

Subjects/Keywords: Multi-period stochastic optimization; Robust optimization; Portfolio optimization; Piecewise quadratic qptimization; Parametric qptimization

Record Details Similar Records

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APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6^{th} Edition):

Morris, C. (2017). Dynamic portfolio optimization using mean-semivariance. (Doctoral Dissertation). Georgia Tech. Retrieved from http://hdl.handle.net/1853/59245

Chicago Manual of Style (16^{th} Edition):

Morris, Carl. “Dynamic portfolio optimization using mean-semivariance.” 2017. Doctoral Dissertation, Georgia Tech. Accessed November 17, 2019. http://hdl.handle.net/1853/59245.

MLA Handbook (7^{th} Edition):

Morris, Carl. “Dynamic portfolio optimization using mean-semivariance.” 2017. Web. 17 Nov 2019.

Vancouver:

Morris C. Dynamic portfolio optimization using mean-semivariance. [Internet] [Doctoral dissertation]. Georgia Tech; 2017. [cited 2019 Nov 17]. Available from: http://hdl.handle.net/1853/59245.

Council of Science Editors:

Morris C. Dynamic portfolio optimization using mean-semivariance. [Doctoral Dissertation]. Georgia Tech; 2017. Available from: http://hdl.handle.net/1853/59245

Princeton University

27.
Matthews, Logan Ryan.
Advancing *Robust* *Optimization* for Process Systems Engineering Applications
.

Degree: PhD, 2018, Princeton University

URL: http://arks.princeton.edu/ark:/88435/dsp01hh63sz60j

► *Robust* *optimization* is a popular method for incorporating parameter uncertainty into *optimization* models. Whether parameters represent the price of a feedstock or product, the operability…
(more)

Subjects/Keywords: Global Optimization; Optimization Under Uncertainty; Process Synthesis; Resilient Network Design; Robust Optimization

Record Details Similar Records

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APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6^{th} Edition):

Matthews, L. R. (2018). Advancing Robust Optimization for Process Systems Engineering Applications . (Doctoral Dissertation). Princeton University. Retrieved from http://arks.princeton.edu/ark:/88435/dsp01hh63sz60j

Chicago Manual of Style (16^{th} Edition):

Matthews, Logan Ryan. “Advancing Robust Optimization for Process Systems Engineering Applications .” 2018. Doctoral Dissertation, Princeton University. Accessed November 17, 2019. http://arks.princeton.edu/ark:/88435/dsp01hh63sz60j.

MLA Handbook (7^{th} Edition):

Matthews, Logan Ryan. “Advancing Robust Optimization for Process Systems Engineering Applications .” 2018. Web. 17 Nov 2019.

Vancouver:

Matthews LR. Advancing Robust Optimization for Process Systems Engineering Applications . [Internet] [Doctoral dissertation]. Princeton University; 2018. [cited 2019 Nov 17]. Available from: http://arks.princeton.edu/ark:/88435/dsp01hh63sz60j.

Council of Science Editors:

Matthews LR. Advancing Robust Optimization for Process Systems Engineering Applications . [Doctoral Dissertation]. Princeton University; 2018. Available from: http://arks.princeton.edu/ark:/88435/dsp01hh63sz60j

Penn State University

28.
Bekiroglu, Korkut.
From Data to Interventions: Using System Identification and
*Robust* Control Algorithms to Design Effective Treatments.

Degree: PhD, Electrical Engineering, 2015, Penn State University

URL: https://etda.libraries.psu.edu/catalog/26227

► Behavioral and social scientists have demonstrated the advantages of the adaptive treatments, which usually provide better results than the fixed treatment (all patients get same…
(more)

Subjects/Keywords: Adaptive Intervention; Robust Treatment Design; System Identification; Atomic Norm; min-max Structured Robust Optimization

Record Details Similar Records

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APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6^{th} Edition):

Bekiroglu, K. (2015). From Data to Interventions: Using System Identification and Robust Control Algorithms to Design Effective Treatments. (Doctoral Dissertation). Penn State University. Retrieved from https://etda.libraries.psu.edu/catalog/26227

Chicago Manual of Style (16^{th} Edition):

Bekiroglu, Korkut. “From Data to Interventions: Using System Identification and Robust Control Algorithms to Design Effective Treatments.” 2015. Doctoral Dissertation, Penn State University. Accessed November 17, 2019. https://etda.libraries.psu.edu/catalog/26227.

MLA Handbook (7^{th} Edition):

Bekiroglu, Korkut. “From Data to Interventions: Using System Identification and Robust Control Algorithms to Design Effective Treatments.” 2015. Web. 17 Nov 2019.

Vancouver:

Bekiroglu K. From Data to Interventions: Using System Identification and Robust Control Algorithms to Design Effective Treatments. [Internet] [Doctoral dissertation]. Penn State University; 2015. [cited 2019 Nov 17]. Available from: https://etda.libraries.psu.edu/catalog/26227.

Council of Science Editors:

Bekiroglu K. From Data to Interventions: Using System Identification and Robust Control Algorithms to Design Effective Treatments. [Doctoral Dissertation]. Penn State University; 2015. Available from: https://etda.libraries.psu.edu/catalog/26227

Clemson University

29.
Dranichak, Garrett M.
* Robust* Solutions to Uncertain Multiobjective Programs.

Degree: PhD, Mathematical Sciences, 2018, Clemson University

URL: https://tigerprints.clemson.edu/all_dissertations/2154

► Decision making in the presence of uncertainty and multiple conﬂicting objec-tives is a real-life issue, especially in the ﬁelds of engineering, public policy making, business…
(more)

Subjects/Keywords: highly robust efficient; objective-wise uncertainty; robust multiobjective optimization; uncertain multiobjective programs

Record Details Similar Records

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APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6^{th} Edition):

Dranichak, G. M. (2018). Robust Solutions to Uncertain Multiobjective Programs. (Doctoral Dissertation). Clemson University. Retrieved from https://tigerprints.clemson.edu/all_dissertations/2154

Chicago Manual of Style (16^{th} Edition):

Dranichak, Garrett M. “Robust Solutions to Uncertain Multiobjective Programs.” 2018. Doctoral Dissertation, Clemson University. Accessed November 17, 2019. https://tigerprints.clemson.edu/all_dissertations/2154.

MLA Handbook (7^{th} Edition):

Dranichak, Garrett M. “Robust Solutions to Uncertain Multiobjective Programs.” 2018. Web. 17 Nov 2019.

Vancouver:

Dranichak GM. Robust Solutions to Uncertain Multiobjective Programs. [Internet] [Doctoral dissertation]. Clemson University; 2018. [cited 2019 Nov 17]. Available from: https://tigerprints.clemson.edu/all_dissertations/2154.

Council of Science Editors:

Dranichak GM. Robust Solutions to Uncertain Multiobjective Programs. [Doctoral Dissertation]. Clemson University; 2018. Available from: https://tigerprints.clemson.edu/all_dissertations/2154

University of Manchester

30.
Diaz Leiva, Juan Esteban.
Simulation-Based *Optimization* for Production Planning:
Integrating Meta-Heuristics, Simulation and Exact Techniques to
Address the Uncertainty and Complexity of Manufacturing
Systems.

Degree: 2016, University of Manchester

URL: http://www.manchester.ac.uk/escholar/uk-ac-man-scw:301199

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This doctoral thesis investigates the application of simulation-based *optimization* (SBO) as an alternative to conventional *optimization* techniques when the inherent uncertainty and complex features of…
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Subjects/Keywords: Combinatorial optimization; Genetic algorithms; Matheuristics; Meta-heuristics; Multi-objective optimization; Production planning; Robust optimization; Simulation-based optimization; Uncertainty modelling

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APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6^{th} Edition):

Diaz Leiva, J. E. (2016). Simulation-Based Optimization for Production Planning: Integrating Meta-Heuristics, Simulation and Exact Techniques to Address the Uncertainty and Complexity of Manufacturing Systems. (Doctoral Dissertation). University of Manchester. Retrieved from http://www.manchester.ac.uk/escholar/uk-ac-man-scw:301199

Chicago Manual of Style (16^{th} Edition):

Diaz Leiva, Juan Esteban. “Simulation-Based Optimization for Production Planning: Integrating Meta-Heuristics, Simulation and Exact Techniques to Address the Uncertainty and Complexity of Manufacturing Systems.” 2016. Doctoral Dissertation, University of Manchester. Accessed November 17, 2019. http://www.manchester.ac.uk/escholar/uk-ac-man-scw:301199.

MLA Handbook (7^{th} Edition):

Diaz Leiva, Juan Esteban. “Simulation-Based Optimization for Production Planning: Integrating Meta-Heuristics, Simulation and Exact Techniques to Address the Uncertainty and Complexity of Manufacturing Systems.” 2016. Web. 17 Nov 2019.

Vancouver:

Diaz Leiva JE. Simulation-Based Optimization for Production Planning: Integrating Meta-Heuristics, Simulation and Exact Techniques to Address the Uncertainty and Complexity of Manufacturing Systems. [Internet] [Doctoral dissertation]. University of Manchester; 2016. [cited 2019 Nov 17]. Available from: http://www.manchester.ac.uk/escholar/uk-ac-man-scw:301199.

Council of Science Editors:

Diaz Leiva JE. Simulation-Based Optimization for Production Planning: Integrating Meta-Heuristics, Simulation and Exact Techniques to Address the Uncertainty and Complexity of Manufacturing Systems. [Doctoral Dissertation]. University of Manchester; 2016. Available from: http://www.manchester.ac.uk/escholar/uk-ac-man-scw:301199